Comment on "Theory of tailoring sonic devices: Diffraction dominates over refraction"

Recently N. Garcia et al. (Phys. Rev. E 67, 046606 (2003)) theoretically studied several acoustic devices with dimensions on de order of several wavelenghts. The authors discussed on experimental results previously reported by several of us (F. Cervera et al., Phys. Rev. Lett. 88, 023902 (2002)). They concluded that diffraction and not refraction is the ominating mechanism that explain the focusing effects observed in those experiments. In this Comment we reexamined their calculations and discussed why some of their interpretations of our results are misleading.Comment: 2 pages, 2 figures, a comment on an articl

The Golden Channel at a Neutrino Factory revisited: improved sensitivities from a Magnetised Iron Neutrino Detector

This paper describes the performance and sensitivity to neutrino mixing parameters of a Magnetised Iron Neutrino Detector (MIND) at a Neutrino Factory with a neutrino beam created from the decay of 10 GeV muons. Specifically, it is concerned with the ability of such a detector to detect muons of the opposite sign to those stored (wrong-sign muons) while suppressing contamination of the signal from the interactions of other neutrino species in the beam. A new more realistic simulation and analysis, which improves the efficiency of this detector at low energies, has been developed using the GENIE neutrino event generator and the GEANT4 simulation toolkit. Low energy neutrino events down to 1 GeV were selected, while reducing backgrounds to the $10^{-4}$ level. Signal efficiency plateaus of ~60% for $\nu_\mu$ and ~70% for $\bar{\nu}_\mu$ events were achieved starting at ~5 GeV. Contamination from the $\nu_\mu\rightarrow \nu_\tau$ oscillation channel was studied for the first time and was found to be at the level between 1% and 4%. Full response matrices are supplied for all the signal and background channels from 1 GeV to 10 GeV. The sensitivity of an experiment involving a MIND detector of 100 ktonnes at 2000 km from the Neutrino Factory is calculated for the case of $\sin^2 2\theta_{13}\sim 10^{-1}$. For this value of $\theta_{13}$, the accuracy in the measurement of the CP violating phase is estimated to be $\Delta \delta_{CP}\sim 3^\circ - 5^\circ$, depending on the value of $\delta_{CP}$, the CP coverage at $5\sigma$ is 85% and the mass hierarchy would be determined with better than $5\sigma$ level for all values of $\delta_{CP}$

Numerical modelling of heat transfer and experimental validation in Powder-Bed Fusion with the Virtual Domain Approximation

Among metal additive manufacturing technologies, powder-bed fusion features very thin layers and rapid solidification rates, leading to long build jobs and a highly localized process. Many efforts are being devoted to accelerate simulation times for practical industrial applications. The new approach suggested here, the virtual domain approximation, is a physics-based rationale for spatial reduction of the domain in the thermal finite-element analysis at the part scale. Computational experiments address, among others, validation against a large physical experiment of 17.5 $\mathrm{[cm^3]}$ of deposited volume in 647 layers. For fast and automatic parameter estimation at such level of complexity, a high-performance computing framework is employed. It couples FEMPAR-AM, a specialized parallel finite-element software, with Dakota, for the parametric exploration. Compared to previous state-of-the-art, this formulation provides higher accuracy at the same computational cost. This sets the path to a fully virtualized model, considering an upwards-moving domain covering the last printed layers

Next generation long baseline experiments on the path to leptonic CP violation

In this paper we quantify the trade-off between setups optimized to be ancillary to Phase II Superbeams or Neutrino Factories and experiments tuned for maximal sensitivity to the subdominant terms of the neutrino transition probability at the atmospheric scale (``maximum discovery potential''). In particular, the theta(13) sensitivity is computed for both Phase I superbeams (JHF-SK and NuMI Off-Axis) and next generation long baseline experiments (ICARUS, OPERA and MINOS). It is shown that Phase I experiments cannot reach a sensitivity able to ground (or discourage in a definitive manner) the building of Phase II projects and that, in case of null result and without a dedicated $\bar{\nu}$ run, this capability is almost saturated by high energy beams like CNGS, especially for high values of the ratio $\Delta m^2_{21}/|\Delta m^2_{31}|$.Comment: 19 pages, 8 figures. Version to appear in PL

Моделирование безопасного поведения водителя на перекрестках с помощью глубинного обучения

Roundabouts provide safe and fast circulation as well as many environmental advantages, but drivers adopting unsafe behaviours while circulating through them may cause safety issues, provoking accidents. In this paper we propose a way of training an autonomous vehicle in order to behave in a human and safe way when entering a roundabout. By placing a number of cameras in our vehicle and processing their video feeds through a series of algorithms, including Machine Learning, we can build a representation of the state of the surrounding environment. Then, we use another set of Deep Learning algorithms to analyze the data and determine the safest way of circulating through a roundabout given the current state of the environment, including nearby vehicles with their estimated positions, speeds and accelerations. By watching multiple attempts of a human entering a roundabout with both safe and unsafe behaviours, our second set of algorithms can learn to mimic the human’s good attempts and act in the same way as him, which is key to a safe implementation of autonomous vehicles. This work details the series of steps that we took, from building the representation of our environment to acting according to it in order to attain safe entry into single lane roundabouts

Variables That Influence Articulation Accuracy in Children with Down Syndrome and Specific Language Disorder: Similarities and Differences

Research about speech sound disorders (SSD) in children with Down syndrome (DS) and children with specific language impairment (SLI) suggests similar linguistic profiles with weakness in phonology skills. The question is if these similarities are superficial or share deficits in levels and underlying skills to its speech disorders: phonological memory (PM), coordination motor skills, and articulatory muscular system. Our research involved 24 children divided into four groups: SLI, DS, and two groups of typical development. SLI group presented a mild‐moderate speech disorder and DS group moderate‐severe. Following skills were evaluated: nonverbal intelligence, PM, and oral motor coordination (oral‐DDK). The Iowa Oral Performance Instrument (IOPI) was used for the measurement of physiological variables (strength and endurance of tongue and lips). Percentage of consonants correct (PCC) was found. Phonological memory, motor coordination, and physiological variables are factors associated with SSD in teenagers with DS. However, SSD in children with SLI only are associated to phonological memory. Motor coordination and physiological variables are not involved in their SSD of mild and moderate‐severe levels. We have objectively measured the strength and endurance of tongue and lips. This may have clinical implications. It is necessary to assess objectively all the variables affecting articulatory accuracy to design intervention programs in SSD